Josh BeckmanOf course, if you already know the exact weights you want to assign to each dimension (i.e., you know your utility function), you reduce the problem to a single objective optimization. This is because you can combine the dimensions with the weights into a single quantity to optimize (often called utility, cost, or fitness). In that case, you donât need Pareto at all.
But youâre often faced with situations where your utility function is unknown or uncertain. In those situations, the Pareto front helps you eliminate objectively all the sub-optimal options. It wonât reveal the one best option right from the outset, but you may now experiment with these efficient options and select the one that fits you the best.
Antoine MayerowitzMario Meets Pareto: Multi-Objective Optimization of Mario Kart Builds